Protein-peptide interactions: peptide identification, binding prediction and design
- Pierre Tuffery (UMRS 973, Univ. Paris Diderot, France)
- Martin Zacharias (Technical University of Munich, Germany)
- Angelita Rebollo (CIMI - Univ. Pierre et Marie Curie, France)
- Madji hochlaf (CECAM-FR-MOZER, France)
In the recent years, biologics have emerged as a promising alternative to small compounds for the development of the next generation of therapeutic compounds. Among them, peptides are a specific class of molecules that are involved in cell signaling and trafficking, can act as antibiotics, or can target protein-protein interactions. Following efforts to overcome some of their traditional limitations to make them promising drug candidates have resulted (I) in a better control of their bioavailability (improved resistance to degradation), (ii) improved biodelivery (routes of delivery now include, and rely on different strategies such as the use of nanoparticles or cell penetrating peptides that can specifically target cell lines or organites), and (iii) lower manufacturing costs for larger scale production capacity, to cite some. There are presently over 60 peptide drugs on the market and over 500 in development [1-3].
On the in silico side however, peptide design faces specific challenges. Strategies for peptide design largely differ from those developed for small compounds. Owing to the largely differing physico-chemical properties of both classes of compounds (e.g. size, flexibility), the use of the protocols that have been optimized over decades for chemical drugs is largely inappropriate. Peptides largely escape the rule of five defined by Lipinsky for small compounds. In order to prevent rapid degradation and to improve membrane permeability it is often necessary to chemically modify peptides or to constrain their conformation (e.g. cyclisation) , challenging current in silico methods for peptide modeling and design. Peptide structure modeling, peptide interaction with their targets, the design of peptide sequence variants with improved affinities, specificities and pharmacological profile, their combination with delivery vectors remain challenges to address that motivate the development of optimized and specific protocols[5,6].
Recent new algorithmic methods and developments result in improved force field description of peptides and proteins, much longer accessible simulation time scales for studies in aqueous solution but also promise to overcome some of the challenges for peptide design [7,8]. The in silico peptide community is progressing rapidly, but so far, no synthesis of the specific efforts undertaken has been achieved, which motivates this application and could promote further in silico method advancements. The planned CECAM workshop will bring together about 30-40 computational biophysicists, peptide modelers, bioinformaticians as well as experimentalists designing peptides to interfere with protein-protein interactions. The main aim of the workshop is to critically discuss the state of the art of in silico methods and how to exploit it for more realistically predicting peptide-protein complex structures and rational peptide design. The workshop will be open to participants from the scientific community and pharmaceutical industry.
This workshop will focus on the following objectives:
Session 1/ Molecular simulations to characterize peptide conformation.
It will include:
- the calculation of the conformation of linear and cyclic peptides (head to tail, depsi-peptides, disulfide bonded peptides), and peptides including unusual amino-acids and/or D-amino acids, and their impact on peptide structural properties.
- efforts for improved force field descriptions for peptides but also methodological advances in sampling and free energy simulations to elucidate the relative stability of peptide conformations
- bioinformatics (database) approaches for peptide structure prediction coupled with the inclusion of conformational constraints.
Session 2/ Protocols to characterize protein-peptide interactions.
It will include:
- blind and local docking approaches to characterize binding side, peptide pose, in the context of preserved receptor conformation but also allostery.
- rigid versus flexible docking, and sampling versus scoring issues, and simulation approaches to estimate kinetic constants of association/dissociation, binding affinities in an semi-quantitative or quantitative perspective.
- bioinformatics approaches (patterns of sequence conservation or correlated mutations) that give hints on protein-peptide interaction sites are also included.
Session 3/ Peptide design for target protein.
It will include:
- approaches to design sequences specifically targeting active sites, protein-protein interactions, in the context of both globular and membrane proteins.
- peptide design based on coarse-grained and threading approaches, or on atomistic approaches.
- structural motif based approaches.
- selecting peptides for disrupting protein-protein interactions.
Applications, emphasis will be put, non exclusively, on protein-peptide docking applied to targets that are of medical importance, such as binding of peptides to immune proteins, peptide epitopes that bind to antibodies, or peptides designed to disrupt protein-protein complexes in the context of cancer.
Session 4/ Experimental approaches to design peptides interfering with protein-protein interactions.
This session is intended to stimulate exchanges between the community of the experimentalists and that of the in silico modeling, and to identify practical experimental issues that could be assisted by present or future in silico approaches.
This part will introduce state of the art experimental approaches such as pepscan, peptide arrays, innovative peptide scanning approaches, and more generally high throughput technologies to identify/optimize peptide sequences that can be applied to the design of peptides interfering with protein-protein interactions. It will also be an opportunity for a survey of new strategies to address critical issues such as peptide cell penetration, cargo delivery, organelle-addressed peptides, epitope mapping and enzyme/enzyme inhibitor interactions.
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